One of the facts that most attracted me was the fact that this reference book is excellent for a great variety of IT roles:

Business Analysts

Data Architects

Business Intelligence/Analytics Consultants

ETL Developers

Application Developers

Enterprise Architects

Enjoy….

Chapter 1: Beyond reporting: Business analytics

The book’s first chapter is devoted to introduce you to some of the usual problems encountered with a report-based approach to analysis. It is explained why creating database reports is not a good idea and how Mondrian can be used to overcome those challenges and some of the characteristics that make Mondrian OLAP analytic engine is the best choice

Chapter 2: Mondrian: A first look

Second chapter starts with a brief overview of the architecture, then you will discover some sort of things you can do with Mondrian. Finally, it is explained how to get data from your operational systems into Mondrian to be used for analysis.

Chapter 3: Creating the data mart

This chapter is focused to Data warehouse architects since unveils the general architecture of an analytic solution and then moves to explore the best database modeling technique for business analytics systems, as you sure know this technique consists on build a Star Schema. Besides Star schema is compared with Third Normal form modeling technique.

The chapter describes the new XML syntax of schemas in Mondrian version 4. Logical elements (Schemas, cubes, attributes and measures) and Physical elements (Tables and columns) are described in detail and how Mondrian acquires the data from the data mart. Besides, Mondrian 3.X obsolete models are mentioned on an upgrade section. Finally, an optimized Time Dimension is created.

Chapter 5: How schemas grow

This chapter describes advanced modeling features.

We will see how to design and use:

Shared Dimensions

Measure Groups (Cubes using more than only one fact table)

Parent-Child hierarchies

Hanger Dimensions for comparing Target vs. Actual values

Calculated Members

Chapter 6: Securing data

This chapter shows how to restrict access to specific data members, dimensions, and even the full schema using Mondrian role based access control security policy. Some of the terms used are the following: SchemaGrant, CubeGrant, DimensionGrant, HierarchyGrant, MemberGrant, Measure Grants…

Chapter 7: Maximizing Mondrian Performance

This is a very important issue, since it is focused in describing the different techniques available to improve Mondrian performance. Configuring Mondrian caches (Community Distributed Cache, Infinispan and Memcached), tuning database and creating aggregate tables are some of the techniques mentioned.

Chapter 8: Dynamic Security

This chapter is a continuation of chapter 6 and explains how to manage advanced security requirements in Mondrian by means of using a Dynamic Schema Processor. A DSP allows a dynamic creation of a Mondrian schema made to measure to the connected user. Previous knowledge of Java language is required.

Chapter 9: Working with Mondrian and Pentaho

This chapter takes a look at a good deal tools that are frequently used with Mondrian and show how they are used.

Community Dashboard Framework: Open source tool that allows users to create dashboards using Mondrian data, included in Ctools suite.

Pentaho Report Designer: Open source desktop application that allows users to create pixel perfect reports using Mondrian as an origin of data.

Pentaho Data Integration: Open source ETL tool (aka kettle) which is commonly used to populate the data used by Mondrian as mentioned in previous chapters, but that can also use Mondrian as a source of data.

Chapter 10: Developing with Mondrian

This chapter is focused to software developers and unveils several possibilities to embed Mondrian engine into your custom applications.

In this final chapter it is covered how to do advanced analytics using the enormous power of MDX language both inside Mondrian and with external tools. This complex analytics, through MDX, meets many use cases like Growth, Profitability and Ratios.

Apart from that it is explained some limited What-If Analysis (aka. scenarios) support to allow Mondrian to help you model and think about several “What would occur if X occurred “. Then it is covered how to do inside Mondrian Data mining and Machine Learning using R language or Weka framework such as Clustering, Forecasting or Fraud Detection analysis. Finally it is briefly covered where Mondrian fits within the Big Data ecosystem

Explains how to use the virtual machine with Pentaho CE configured with Mondrian, Saiku and Ctools included in the book.

B Online Resources

Lists all available community resources like blogs and wikis

Summarizing, although the softbound print will not be available until August 2013. I will strongly recommend you don’t lose the opportunity to purchase this wonderful book now on an early access program.

In this quick post I will show the way to quit “JPivot has been replaced by Pentaho Analyzer…” message in Pentaho BI Server CE 4.5 or 4.8 and it is also useful for Pentaho BI Server CE version 3.10.0 stable.

The annoying message is the following

JPivot has been replaced by Pentaho Analyzer.
It is provided as a convenience but will no longer be enhanced or offically supported by Pentaho.

Recently interest in the upcoming Mondrian 4 has increased and as it reaches a more useable state, and Pentaho have started publishing builds to their Artifactory repo, I decided to put together a Saiku & Mondrian 4 build.